BIOCOMPLEXITY: Hexapod Phylogenomics - Bringing Phylogenetic Supercomputing to the Masses

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0120718WhitingA Biocomplexity in the Environment: Genome-Enabled grant has been awarded to an interdisciplinary team of researchers at the Brigham Young University that combines expertise in computer science, statistics, and phylogenetic systematics to address three fundamental questions in evolutionary biology, genomics, and computational biology. (1) What are the major relationships among Hexapods (insects and related taxa)? (2) How has mitochondrial genome evolution occurred relative to Hexapod diversity? (3) How can we develop fast, parallel computer algorithms to reconstruct phylogenetic relationships for large data sets? To answer these questions, the investigators will sequence about 2500 species across hexapod diversity for about 12 nuclear genes representing a total sequencing effort of 30 million base pairs. They will then sequence about 120 mitochondrial genomes across the major lineages representing each of the hexapod orders to examine mitochondrial genome evolution in the context of a well established phylogeny from the 12 nuclear genes. This represents another 1.8 million nucleotides of sequence. Parallel-processing algorithms will be developed for computational analysis of large nucleotide sequence data sets. The results will provide a framework for understanding Hexapod diversity (crucial for understanding agricultural pests, disease vectors, etc.), mitochondrial genome evolution (instrumental in understanding the functional significance of gene rearrangements), and easily available parallel approaches for phylogenetics. Because phylogenetics is becoming an instrumental tool in the study of human disease (both due to infection and the genetic component of complex diseases such as cancer and coronary artery disease), the ability to reconstruct phylogenetic relationships accurately and with great speed for ever-increasing data sets is key to making the link between genetic changes and disease risk factors. The investigators will heavily involve undergraduates, graduate students, and postdoctoral fellows in every phase of this work and provide outlets in the form of publications and informational websites.DEB-0120719Michael Whiting, Keith Crandall, Mark Clement, Quin Snell, David WhitingA grant has been awarded to an interdisciplinary team of researchers at the Brigham Young University that combines expertise in computer science, statistics, and phylogenetic systematics to address three fundamental questions in evolutionary biology, genomics, and computational biology: 1) What are the major relationships among Hexapods (insects and related taxa)? 2) How has mitochondrial genome evolution occurred relative to Hexapod diversity? And 3) how can we develop fast, parallel computer algorithms to reconstruct phylogenetic relationships for large data sets? To answer these questions, the investigators will sequence ~2500 species across hexapod diversity for ~12 genes representing a total sequencing effort of 30 million base pairs. They will then sequence ~120 mitochondrial genomes across the major lineages representing each of the hexapod orders to examine mitochondrial genome evolution in the context of our well established phylogeny from the 12 nuclear genes. This represents another 1.8 million nucleotides of sequence. Finally we will develop parallel algorithms for computational analysis of nucleotide sequence data. The results will provide a framework for understanding Hexapod diversity (crucial for understanding agricultural pests, disease vectors, etc.), mitochondrial genome evolution (instrumental in understanding the functional significance of gene rearrangements), and easily available parallel approaches for phylogenetics. Since phylogenetics is becoming an instrumental tool in the study of human disease (both due to infection and the genetic component of complex diseases such as cancer and coronary artery disease), the ability to reconstruct phylogenetic relationships accurately and with great speed for ever-increasing data sets is key to making the link between genetic changes and disease risk factors. The investigators will heavily involve undergraduates, graduate students, and postdoctoral fellows in every phase of this work and provide outlets in the form of publications and informational websites.